 Hey, welcome back everyone. Live Cube coverage here in the broadcast booth at VMware Explorer. I'm John Furrier, my co-host Dave Vellante. Also my co-host in the Cube pod. Check out the Cube podcast. Every week we break down all the action. Go to siliconangle.com for all the stories. Of course the cube.net, you'll find all the videos there. And today, this session, we're going to review the amazing panel we had yesterday modernizing the digital first multicloud world sponsored by Kindle. We're here with Sunil Bhargava, who's the senior VP of offerings with Kindle to review and just talk about the impact of that panel. We had Oracle Cloud, Azure Cloud, VMware, and of course Kindle. Very dynamic conversation. We're going to unpack that and more here. Dave, what a great conversation. Sunil, great to see you. Thanks for coming back on. Absolutely. It was wonderful to be here yesterday and happy to be here today. This is kind of like a backstage kind of review post-mortem. It was such a good video that we wanted to do on a replay, but also dig deeper because we hit on a bunch of things. Number one, I'll just summarize. The Oracle and Azure together on there with VMware showed multiple vendors talking multicloud in a way that was very productive. They were cooperative. They were talking to each other. They were open and a little bit of a debate, but not much debate. We're all on the same page. Yep. That I think was the biggest takeaway for our customers. What would normally be considered competitors actually sitting ready to cooperate for multicloud for the benefit of customers. Now what we discussed yesterday was many customers end up in multicloud. And now that they're there, you have the issues of policy, of skills that you have to naturally work on. And yes, companies like Kindrel can help address those issues. I use some of our talk. Okay, continue. Yeah, the one thing that we didn't get to cover so much is the deliberate move to multicloud and the new architectural concerns and the new culture concerns that come. And why would you need to do that? As the clouds diverge with the investments they are all making, the opportunity to truly leverage the best of each of the vendor partners we have to get lower economies, faster agility, and really start addressing the needs of JNAI and other operational requirements. That's the real opportunity. Well, and the Oracle Microsoft example is interesting because that's an example of a deliberate attempt to simplify, we were at SuperCloud 2 and I used that example with Insec Ray, who's a VC and he's like, you lost me at Oracle. I'm like, no, that's not fair because what they're doing is actually making it transparent to customers. So that was a big, to us, a big step in that deliberate, what you're calling a deliberate move to multicloud. That's exactly right. And some of the announcements that we have heard this week at VM Explorer are all about making that easier. Being able to do the multicloud architectures, apply policy, modernize more rapidly, and I'm really looking forward to bringing those technologies to our customers. Now that said, the press releases from Microsoft Oracle Center, they make it sound like you just show up and everything works just perfectly. So what role does Kindrel play in actually achieving that simplification and more importantly, realizing that customer value because that's really all about? That's a really good question. So all of these vendors are making the technology part easier and easier to do. But the plethora of technologies requires a skill set that now needs to be a mile wide. And the second is all the nuances of the customer situation, whether it's policy, compliance, data protection, integrations, and some challenges around latency and others that aren't quite available to be absorbed by GenAI, aren't available to be absorbed by code, it really requires knowledge and experience. That's the value Kindrel brings, whether it is to modernize or to operate. So a lot of that is architectural and some companies have that in-house expertise. Many don't or maybe they don't have the bandwidth. Then you've got security concerns and we could talk for hours about the menu of things you've got to deal with. And the architectural about what is the existing state versus the multi-cloud architecture, two different skill sets. And you need access to both to get the job done. Let's take it to the deliberate move, why you see it. And first, I want to tell you a story last night. After the panel, we were out at the VMware Executive mixer and then we met up with you guys later. I've been using that line like multi-clouds, like a collection of things, broken toys or toys you use once in a while. They don't really work well together. I got teams over here. I might have something in, it was here, I used Google for some BigQuery. It's not threaded together, it's not running. And so, which is what we call SuperCloud, that kind of operating model. And the feedback we're hearing from customers, I asked the VMware folks is like, customers are driving the change, not so much the clouds. The clouds will be multi-cloud enabled with technology, but the customers are asking for stuff to work better together. So, and they agreed, you made this point yesterday in the panel, I want to get your thoughts. What is the deliberate move to the cloud look like? Why? What's the motivation? What's the starting point? What's the attitude of the customer? Are they apprehensive? Are they just hostile? I got to get to the cloud. Are they enthusiastic? What's the attitude of the customer as they move to the cloud? What's inspiring them? That's a great point. You know, the move to a cloud was always hampered with security concerns and not being able to physically touch the hardware you own. People have gotten over that, but the conversation remained which cloud? Due to acquisitions, technology introduction, teams preference, customers have found themselves being on multiple clouds today, and now wondering how do you apply policy consistently? Security policy, compliance policy, fiscal policy, whatever policy, how do you apply that consistently? So as we begin to help customers do that, the realization comes in, we no longer have to choose one cloud. We can actually exploit the best of all the existing clouds that we already have in our enterprise. That realization, that having addressed policy and now moving to architecture, having skills on hand through a delivery partner like Kindrel actually creates an opportunity that frankly was too expensive earlier. Great call out, I wanted you to get that out there, but I don't want to throw a wrinkle in here. One is how AI has changed the conversation, because now we're talking about data, and another point that was made by the hyperscalers was by unbundling the focus on the applications and pulling the data out of the app was an interesting comment, because now data becomes the key element to watch between the cloud-migrate movement. So okay, have multiple clouds, there might be separate applications, but now I have data that can be harvested and leveraged by AI, that kind of shines the light on it and too creates a mandate. It absolutely does, and it started at the edge. Data was being generated at the edge for the longest time, but only in the last five years or so were we able to start harvesting it, synthesizing it, pre-processing it, sharing it back home. Now that problem which existed only at the edge now exists across every one of the multi-cloud landing zones that our customers have. The technology, the methodologies, the architectures that people had done, used for multi-tiered data analysis is one of the routes to use on multi-cloud. There are other routes, some of the vendors, as you mentioned, Oracle and Azure in particular are working together to make data access easier, but GenAI, the biggest challenge it's posing, is data management, policy around it, knowing what you're allowed to use and what you're not allowed to use, and making sure that when you use GenAI to make productions, are you actually using a representative data set? Can you trust the outcome? That really puts a big shine on data. It's not just making the plumbing work. There's a data strategy, there's legal and compliance issues. The other thing, too, I would say, John and Sunil, is just in observing the year of AI, there are a lot of, and we buy the premise that you need to have this sort of, what VMware's calling private AI. Private AI, yes. Because of the legal issues, John, you and I have talked about this a lot, we've done a lot of research in it as well, our power law, distribution of AI, so it all makes sense, but when you look around at what's available for customers to actually deploy, you get a lot of stuff in the cloud. If I want to do things in a hybrid or a multi-cloud or even a non-prem fashion, I see reference architectures, I see a lot of complexity, I see a lot of immaturity, and so that's, again, where you guys bring skillsets. How do you think about bringing that to market for customers, are you getting a lot of demand for, hey, help? We don't really understand how to make this stuff work. What are the dimensions that they're asking for help in? That's a great point. So complexity is one of the biggest challenges they end up facing, and generally with complexity comes elongated timelines. What our customers are bringing us to us is the desire for agility through minimum viable product that can iterate, deliver value to the organization, because some of the things they're now stepping into are actually culture changes within their organization. So waiting for a perfect solution is not really what they're looking for. They're looking for iterative solutions that give insights, allows them to do the change management, skill development, funding, clarity, while continuing to progress on this journey. So that actually puts a point that we had talked about yesterday with managed services and how managed services now becomes in parallel to this innovation. Enabling it, supporting it, no longer transform first and then manage later, but rather doing it in parallel streams. Sonia, we've been following Kindrel since the launch of the venture, the renaming and seeing the success of it. And now with the whole AI and multi-cloud, it's much more mainstream in the sense of the urgency that they're in. What attracted you to join Kindrel? And how do you see the role of Kindrel orchestrating and leading this transformation on behalf of customers? That's a great question, John. Thank you. So Kindrel has 75 of the top, 100 Fortune, 100 companies, equally large number of the Fortune 500, all the major banks. And they have some of the most complex environments, but the innovation drivers they have and what they can do for their customers also poses a great opportunity. So when I was looking, I concluded that that opportunity is probably the richest. Then the next question is, is Kindrel set to actually achieve the opportunity there? And what we find in Kindrel, enormous customer-centric scientists, customer-centric delivery personnel, customer-centric teams, and I'm really excited about the energy in our company to help customers achieve the value from Kindrel. And that requires a variety of operating models. Some customers want to in-source part, outsource part, collaborate in co-sourcing. Those various operating models is one of the strengths of Kindrel. And for that reason, I think I wanted to join a company that's best positioned structurally to really achieve success in this hybrid world where it's not just clouds that are hybrid, but the entire way IT is delivered is becoming hybrid, but DevSecOps, at the same time as Cots applications, all intertwined delivering value. And I'm excited to see that my suspicions about this being the company that can deliver it, turning out to be true. You were talking earlier about the thinking about the management and the transformation together as sort of a parallel exercise. But when a customer comes to you and says, okay, help us figure out our AI strategy, you got us data is obviously a critical piece of that. Given you've got application, portfolio, there's an opportunity to modernize that. Are those also parallel efforts or do you take those sequentially? In other words, hey, you got to get your data order in order before you can even think about that or do you sort of in parallel think about your application portfolio and all the business impacts? Another great question. So your question started off with strategy. Strategy has to be done in parallel. Execution can be serialized and sometimes it needs to be, but strategies always needs to be done in parallel so that you're not coming back to revisit decisions you made. Because of the highly iterative ways delivery happens now, execution not just serialized, but sometimes leading, sometimes trailing. We do see that happening as well. Sunil, great to have you back on. What a great panel. Kendrill did yesterday. I think the panel yesterday that you led with your partners kind of encapsulates multi-cloud. It really did. It really did. There was good conversations, honest, intellectually honest, people were engaged. I've never seen anything like it. It was a very big success. I want to thank you for doing that. We really appreciate it. Thanks for coming back on. To give us more insight into your vision and Kendrill. Thank you very much. Okay, it's theCUBE. We're live here in Las Vegas, the broadcast booth in VMware Explore. This is theCUBE. SiliconANGLE on theCUBE. Go to SiliconANGLE.com. Check out our new theCUBEAI.com. That's our special language model. Also go to theCUBE.net for this video and all of our videos from VMware as well. On YouTube, Twitter, and all the social world. All our channels are open. Contact Dave and I for Dave Vellante. I'm John Furrier. We'll be back with more live coverage after this short break.